<teaser>A <a href="http://bioinformatics.oxfordjournals.org/cgi/content/abstract/btq130">new application note</a> has been published recently in Bioinformatics, about the '''isa''' and '''eisa''' packages and the Iterative Signature Algorithm.

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<date>24 Jul 2010 — 17:49</date>

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</teaser>

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[[image:expmat.png|An ISA transcription module|300px|right|link=ISA]]

[[image:expmat.png|An ISA transcription module|300px|right|link=ISA]]

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Large sets of data, like expression profile from many samples, require

Large sets of data, like expression profile from many samples, require

The '''Iterative Signature Algorithm (ISA)''' was designed to reduce the

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("clusters"). Yet, in some cases overlapping cluster assignments would suit

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the biological reality much better.

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The '''Iterative Signature Algorithm (ISA)''' was designed to overcome this and

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other limitations of standard clustering algorithms. It aims to reduce the

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complexity of very large sets of data by decomposing it into so-called

complexity of very large sets of data by decomposing it into so-called

"modules". In the context of gene expression data these modules consist of

"modules". In the context of gene expression data these modules consist of

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We developed the <code>eisa</code> [http://www.r-project.org GNU R] package to facilitate the modular analysis of gene expression data. The package uses standard [http://www.bioconductor.org BioConductor] data structures and includes various visualization tools as well.

We developed the <code>eisa</code> [http://www.r-project.org GNU R] package to facilitate the modular analysis of gene expression data. The package uses standard [http://www.bioconductor.org BioConductor] data structures and includes various visualization tools as well.

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=== Requirements ===

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=== Requirements, download and installation ===

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To use <code>eisa</code> you will need a working [http://www.r-project.org GNU R] and [http://www.bioconductor.org BioConductor] installation. You will also need the <code>isa2</code>, <code>Category</code> and <code>genefilter</code> R packages. You can install these by typing

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To use <code>eisa</code> you will need a working [http://www.r-project.org GNU R] installation.

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install.packages("isa2")

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As of the 23rd of April, 2010, the <code>eisa</code> package is an official [http://www.bioconductor.org BioConductor] package.

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source("http://bioconductor.org/biocLite.R")

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biocLite(c("Category", "genefilter"))

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at your R prompt.

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<code>eisa</code> depends on a number of other R packages: <code>isa2</code>, <code>Biobase</code>, <code>AnnotationDbi</code>, <code>Category</code>, <code>genefilter</code>, <code>DBI</code>. The good news is that all these dependencies are installed automatically, and all you need to do is to start R and type in

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=== Download and Installation ===

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source("http://bioconductor.org/biocLite.R")

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biocLite("eisa")

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at your R prompt. See [http://bioconductor.org/packages/release/bioc/html/eisa.html the eisa package page at the BioConductor website] for details.

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The <code>eisa</code> package is currently being reviewed by the BioConductor team. Until it is available from the standard BioConductor repositories, it can be downloaded from here. The most recent version of the <code>eisa</code> package is 0.2. Please follow the installation instructions for your platform.

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Alternatively, you can also download the package from here:

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* '''[http://www.unil.ch/cbg/homepage/downloads/eisa_0.2.2.zip Microsoft Windows (all versions)]''' <br/>Download [http://www.unil.ch/cbg/homepage/downloads/eisa_0.2.2.zip this file], save it in a temporary directory, and then start R. From the Packages menu choose '<code>Install packages from local zip files</code>' and select the saved file.

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* '''[http://www.unil.ch/cbg/homepage/downloads/eisa_1.0.0.zip Microsoft Windows (32 bit)]''' <br/>Download [http://www.unil.ch/cbg/homepage/downloads/eisa_1.0.0.zip this file], save it in a temporary directory, and then start R. From the Packages menu choose '<code>Install packages from local zip files</code>' and select the saved file.

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* '''Mac OSX (all versions)''' <br/> Currently not available.

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* '''[http://www.unil.ch/cbg/homepage/downloads/win64/eisa_1.0.0.zip Microsoft Windows (64 bit)]''' <br/>Download [http://www.unil.ch/cbg/homepage/downloads/win64/eisa_1.0.0.zip this file], save it in a temporary directory, and then start R. From the Packages menu choose '<code>Install packages from local zip files</code>' and select the saved file.

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* '''[http://www.unil.ch/cbg/homepage/downloads/eisa_0.2.2.tar.gz Linux and Unix systems, R source package]''' <br/> Download [http://www.unil.ch/cbg/homepage/downloads/eisa_0.2.2.tar.gz this file], save it in a temporary directory, and start R. Install the downloaded package using the <code>install.packages()</code> function: give the full path of the saved file and use the '<code>repos=NULL</code>' argument of <code>install.packages()</code>.

* '''[http://www.unil.ch/cbg/homepage/downloads/eisa_1.0.0.tar.gz Linux and Unix systems, R source package]''' <br/> Download [http://www.unil.ch/cbg/homepage/downloads/eisa_1.0.0.tar.gz this file], save it in a temporary directory, and start R. Install the downloaded package using the <code>install.packages()</code> function: give the full path of the saved file and use the '<code>repos=NULL</code>' argument of <code>install.packages()</code>.

=== License ===

=== License ===

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=== Requirements ===

=== Requirements ===

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No additional R package is required to install and use <code>isa2</code>. But on Linux and Unix systems you will need a C compiler to install it. E.g. on Ubuntu Linux you will need to install the '<code>build-essential</code> package.

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No additional R package is required to install and use <code>isa2</code>. But on Linux and Unix systems you will need a C compiler to install it. E.g. on Ubuntu Linux you will need to install the <code>build-essential</code> package.

You can download it from [[here]]. It includes the implementation of the Ping-pong algorithm [ref].

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[[ISA internals|HTML]]

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[http://www2.unil.ch/cbg/homepage/downloads/ISA_internals.pdf PDF]

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[http://www2.unil.ch/cbg/homepage/downloads/ISA_internals.Rnw Rnw]

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[http://www2.unil.ch/cbg/homepage/downloads/ISA_internals.R R code]

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=Matlab package=

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You can download it from [[Media:ISApackage-1.03.zip|here]]. It also includes the implementation of the Ping-pong algorithm <cite>Kutalik2008NB</cite>.

= Papers =

= Papers =

Revision as of 17:07, 20 August 2012

Large sets of data, like expression profile from many samples, require
analytic tools to reduce their complexity.
The Iterative Signature Algorithm (ISA) was designed to reduce the
complexity of very large sets of data by decomposing it into so-called
"modules". In the context of gene expression data these modules consist of
subsets of genes that exhibit a coherent expression profile only over a
subset of microarray experiments. Genes and arrays may be attributed to
multiple modules and the level of required coherence can be varied resulting
in different "resolutions" of the modular mapping. Since the ISA does not
rely on the computation of correlation matrices (like many other tools), it
is extremely fast even for very large datasets.

Requirements, download and installation

As of the 23rd of April, 2010, the eisa package is an official BioConductor package.

eisa depends on a number of other R packages: isa2, Biobase, AnnotationDbi, Category, genefilter, DBI. The good news is that all these dependencies are installed automatically, and all you need to do is to start R and type in

Linux and Unix systems, R source package Download this file, save it in a temporary directory, and start R. Install the downloaded package using the install.packages() function: give the full path of the saved file and use the 'repos=NULL' argument of install.packages().

License

Software for any tabular data

The ISA can be applied to identify coherent substructures (i.e. modules) from any rectangular matrix of data. You can use the isa2 R package for such an analysis.

Requirements

No additional R package is required to install and use isa2. But on Linux and Unix systems you will need a C compiler to install it. E.g. on Ubuntu Linux you will need to install the build-essential package.

Installation

The isa2 package is available from CRAN, the standard R package repository. You can install it on any platform that is supported by GNU R, e.g. Microsoft Windows, Mac OSX and Linux systems. To install it, start R and type in

install.packages("isa2")

at the prompt. On Linux and Unix-like systems, you will need a working C compiler for a successful installation.

License

The isa2 package is licensed under the Creative Commons Attribution-Noncommercial-Share Alike 3.0 License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-sa/3.0/ or send a letter to Creative Commons, 171 Second Street, Suite 300, San Francisco, California, 94105, USA.